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首页> 外文会议>Conference on biomedical applications in molecular, structural, and functional imaging >3D Graph-Based Automated Segmentation of Corneal Layers in Anterior-Segment Optical Coherence Tomography Images of Mice
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3D Graph-Based Automated Segmentation of Corneal Layers in Anterior-Segment Optical Coherence Tomography Images of Mice

机译：基于3D图的小鼠前段光学相干断层扫描图像中的角膜层自动分割

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Anterior segment optical coherence tomography (AS-OCT) is a non-invasive imaging modality that allows for the quantitative assessment of corneal thicknesses. Automated approaches for these measurements are not readily available and therefore measurements are often obtained manually. While graph-based approaches that enable the optimal simultaneous segmentation of multiple 3D surfaces have been proposed and applied to 3D optical coherence tomography volumes of the back of the eye, such approaches have not been applied for the segmentation of the corneal surfaces. In this work we propose adapting this graph-based method for the automated 3D segmentation of three corneal surfaces in AS-OCT images and to measure total corneal thickness. The approach is evaluated based on 34 AS-OCT volumes obtained from both eyes of 17 mice with varying corneal thicknesses. The segmentation accuracy was assessed using unsigned border positioning errors and was found to be 1.82 ± 0.81 μm. We also assessed an average relative error in total layer thickness measurements which was found to be 2.27%.
机译：前段光学相干断层扫描（AS-OCT）是一种非侵入性的成像方式，可以定量评估角膜厚度。这些测量的自动化方法尚不可用，因此通常是手动获得测量值。虽然已经提出了能够对多个3D表面进行最佳同时分割的基于图的方法，并将其应用于眼后的3D光学相干断层扫描体积，但此类方法尚未应用于角膜表面的分割。在这项工作中，我们建议采用这种基于图的方法对AS-OCT图像中的三个角膜表面进行自动3D分割，并测量总的角膜厚度。该方法是根据从17只小鼠的两只眼睛中获得的34种AS-OCT体积（具有不同的角膜厚度）进行评估的。使用无符号边界定位误差评估了分割精度，发现分割精度为1.82±0.81μm。我们还评估了总层厚度测量中的平均相对误差，发现该平均相对误差为2.27％。

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